Nonparametric hypothesis testing for equality of means on the simplex
In the context of data that lie on the simplex, we investigate use of empirical and exponential empirical likelihood, and Hotelling and James statistics, to test the null hypothesis of equal population means based on two independent samples. We perform an extensive numerical study using data simulat...
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| Format: | Article |
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Taylor & Francis
2016
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| Online Access: | https://eprints.nottingham.ac.uk/43849/ |
| _version_ | 1848796781544996864 |
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| author | Tsagris, Michail Preston, Simon P. Wood, Andrew T.A. |
| author_facet | Tsagris, Michail Preston, Simon P. Wood, Andrew T.A. |
| author_sort | Tsagris, Michail |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In the context of data that lie on the simplex, we investigate use of empirical and exponential empirical likelihood, and Hotelling and James statistics, to test the null hypothesis of equal population means based on two independent samples. We perform an extensive numerical study using data simulated from various distributions on the simplex. The results, taken together with practical considerations regarding implementation, support the use of bootstrap-calibrated James statistic. |
| first_indexed | 2025-11-14T19:53:26Z |
| format | Article |
| id | nottingham-43849 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:53:26Z |
| publishDate | 2016 |
| publisher | Taylor & Francis |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-438492020-05-04T18:08:03Z https://eprints.nottingham.ac.uk/43849/ Nonparametric hypothesis testing for equality of means on the simplex Tsagris, Michail Preston, Simon P. Wood, Andrew T.A. In the context of data that lie on the simplex, we investigate use of empirical and exponential empirical likelihood, and Hotelling and James statistics, to test the null hypothesis of equal population means based on two independent samples. We perform an extensive numerical study using data simulated from various distributions on the simplex. The results, taken together with practical considerations regarding implementation, support the use of bootstrap-calibrated James statistic. Taylor & Francis 2016-08-02 Article PeerReviewed Tsagris, Michail, Preston, Simon P. and Wood, Andrew T.A. (2016) Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87 (2). pp. 406-422. ISSN 1563-5163 Compositional data hypothesis testing Hotelling test James test nonparametric empirical likelihood bootstrap http://www.tandfonline.com/doi/abs/10.1080/00949655.2016.1216554 doi:10.1080/00949655.2016.1216554 doi:10.1080/00949655.2016.1216554 |
| spellingShingle | Compositional data hypothesis testing Hotelling test James test nonparametric empirical likelihood bootstrap Tsagris, Michail Preston, Simon P. Wood, Andrew T.A. Nonparametric hypothesis testing for equality of means on the simplex |
| title | Nonparametric hypothesis testing for equality of means on the simplex |
| title_full | Nonparametric hypothesis testing for equality of means on the simplex |
| title_fullStr | Nonparametric hypothesis testing for equality of means on the simplex |
| title_full_unstemmed | Nonparametric hypothesis testing for equality of means on the simplex |
| title_short | Nonparametric hypothesis testing for equality of means on the simplex |
| title_sort | nonparametric hypothesis testing for equality of means on the simplex |
| topic | Compositional data hypothesis testing Hotelling test James test nonparametric empirical likelihood bootstrap |
| url | https://eprints.nottingham.ac.uk/43849/ https://eprints.nottingham.ac.uk/43849/ https://eprints.nottingham.ac.uk/43849/ |